SUPPORT-Paper-ICON@3xCase Study

Pharmaceutical company is reducing the time spent on data curation by 50% with DISQOVER

ONTOFORCE DISQOVER  CASE STUDY Anonymous
Industry

Industry 
Pharmaceutical

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Number of employees
+3,000

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Location 
America

OUR CUSTOMER 

Our customer is an American pharmaceutical company focused on developing treatments and technologies for rare diseases and conditions. 

Use case
  • Disease prioritization

The challenge

Within the universe of rare diseases, our customer needed to choose targets suitable for gene therapy and genomic approaches efficiently.

Choosing the right targets means reviewing a universe of over 7000 rare diseases in multiple data sources. For each specific disease of interest, it is important to determine what clinical trials had been done, what drugs were approved, and what genes were involved. All this information is required to assess which disease areas would be appropriate for a potential therapeutic approach.

Data on rare diseases is particularly disparate, meaning multiple data sources need to be consulted, and there is no possibility to filter by adding criteria in a unified way.

The outcome

By using DISQOVER to filter down from an original 7000 rare diseases, our customer determined which 20 rare diseases to conduct a deeper scientific dive on very quickly. From those 20, they then selected a handful to focus on for therapeutic approaches.

They now have an efficient way to scan through all disorders, with the ability to filter by adding criteria such as prevalence.

Benefits

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All data connected

In ONTOFORCE’s tool DISQOVER the links between different ontologies are available out of the box, meaning the various clinical trials are already linked to the rare diseases.

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Faster to market

Using DISQOVER reduced the time spent gathering data by approximately 50%.

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Clinicaltrials.gov API: easy search

The connection to the clinicaltrials.gov API was very useful and allowed easy searches.

Users find it incredibly useful to have a tool that has already completed the task of linking the ontologies, as this allows them to analyze the competitive landscape on different diseases quickly without the need for time-consuming manual effort.

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